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.env.example

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+# ── Required ──────────────────────────────────────────────────
+# Get your BOT_TOKEN from @BotFather on Telegram
+BOT_TOKEN=your_bot_token_here
+
+# Get API_ID and API_HASH from https://my.telegram.org/apps
+API_ID=12345678
+API_HASH=your_api_hash_here
+
+# ── Optional ───────────────────────────────────────────────────
+# Dashboard port (default 7860 for Hugging Face Spaces)
+PORT=7860

.gitignore

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+node_modules/
+.env
+*.jpg
+*.jpeg
+*.png
+*.log

Dockerfile

@@ -1,27 +1,32 @@
-# Use official Node.js 18 slim image
-FROM node:18-slim
+FROM node:20-slim
 
-# Install git to clone the repository
-RUN apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
+# Install system dependencies for Tesseract OCR and Sharp
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    tesseract-ocr \
+    tesseract-ocr-eng \
+    libtesseract-dev \
+    libgl1-mesa-glx \
+    libvips42 \
+    python3 \
+    python3-pip \
+    ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
 
-# Set the working directory and permissions
+# Set up app directory with correct ownership
 WORKDIR /home/node/app
 RUN chown -R node:node /home/node/app
 
-# Use the existing 'node' user (UID 1000)
 USER node
 ENV HOME=/home/node \
-    PATH=/home/node/.local/bin:$PATH
+    PORT=7860
 
-# The user requested to clone the repo inside the container
-RUN git clone https://github.com/AlexaInc/wordlesolver.git .
+# Install Node dependencies first (layer caching)
+COPY --chown=node:node package*.json ./
+RUN npm install --omit=dev
 
-# Install dependencies 
-RUN npm install
+# Copy source files
+COPY --chown=node:node . .
 
-# Expose the standard Hugging Face Spaces port
 EXPOSE 7860
 
-# Command to start both the web server and the bot
-# Note: Ensure you have set BOT_TOKEN in Hugging Face Secrets!
-CMD ["npm", "start"]
+CMD ["node", "bot.js"]

README.md

@@ -1,10 +1,20 @@
 ---
-title: Wordsolver
-emoji: 📉
-colorFrom: gray
-colorTo: pink
+title: Word Grid Solver Bot
+emoji: 🧩
+colorFrom: blue
+colorTo: indigo
 sdk: docker
 pinned: false
 ---
 
+# Word Grid Solver Bot
+
+High-accuracy Telegram bot for solving word grid puzzles with real-time dashboard.
+
+## Deployment Details
+This Space runs a Docker container with:
+- Node.js (Telegraf, Tesseract.js)
+- Python (EasyOCR)
+- Express Dashboard
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

bot.js

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+/**
+ * bot.js — Word Grid Solver Bot (GramJS / pure MTProto)
+ *
+ * Uses the `telegram` npm package (GramJS) with a BOT_TOKEN for pure MTProto.
+ * No Telegraf, no HTTP Bot API polling — raw MTProto layer.
+ *
+ * Required env vars:
+ *   BOT_TOKEN   – Telegram bot token (from @BotFather)
+ *   API_ID      – Telegram API ID   (from https://my.telegram.org/apps)
+ *   API_HASH    – Telegram API hash (from https://my.telegram.org/apps)
+ *
+ * Optional:
+ *   PORT        – HTTP dashboard port (default 7860)
+ */
+
+'use strict';
+
+require('dotenv').config();
+
+const { TelegramClient } = require('telegram');
+const { StringSession }  = require('telegram/sessions');
+const { NewMessage }     = require('telegram/events');
+
+const express = require('express');
+const fs      = require('fs');
+const path    = require('path');
+
+const { extractGrid } = require('./ocr');
+const { solve }       = require('./solver');
+
+// ─── Environment ──────────────────────────────────────────────────────────────
+const BOT_TOKEN = process.env.BOT_TOKEN;
+const API_ID    = parseInt(process.env.API_ID  || '0', 10);
+const API_HASH  = process.env.API_HASH || '';
+
+if (!BOT_TOKEN) {
+  console.error('[FATAL] BOT_TOKEN is required.');
+  process.exit(1);
+}
+if (!API_ID || !API_HASH) {
+  console.error('[FATAL] API_ID and API_HASH are required for GramJS MTProto.');
+  console.error('        Get them from https://my.telegram.org/apps');
+  process.exit(1);
+}
+
+// ─── Dictionary ───────────────────────────────────────────────────────────────
+const dictionaryPath = path.join(__dirname, 'node_modules/check-word/words/en.txt');
+const dictionary = new Set();
+try {
+  const data = fs.readFileSync(dictionaryPath, 'utf8');
+  for (const line of data.split('\n')) {
+    const w = line.trim().toLowerCase();
+    if (w.length >= 3) dictionary.add(w);
+  }
+  console.log(`[Dict] Loaded ${dictionary.size} words.`);
+} catch (err) {
+  console.error('[Dict] Failed to load dictionary:', err.message);
+}
+
+function isWord(w) {
+  return dictionary.has((w || '').toLowerCase());
+}
+
+// ─── Stats ────────────────────────────────────────────────────────────────────
+const stats = {
+  imagesProcessed: 0,
+  wordsFound:      0,
+  startTime:       Date.now(),
+  botUsername:     'loading...',
+};
+
+// ─── Utility helpers ──────────────────────────────────────────────────────────
+function sleep(ms) {
+  return new Promise(r => setTimeout(r, ms));
+}
+
+async function deleteFile(filePath) {
+  for (let i = 0; i < 5; i++) {
+    try {
+      if (fs.existsSync(filePath)) fs.unlinkSync(filePath);
+      return;
+    } catch (_) {
+      await sleep(800);
+    }
+  }
+}
+
+// ─── Caption parsers ──────────────────────────────────────────────────────────
+/**
+ * Parse word patterns from caption text — single left-to-right pass.
+ * Supports all of:
+ *   M--- (4)          → pattern + explicit length hint
+ *   M----             → standalone dashes (2+ required)
+ *   W---- H--- (4)    → multiple patterns on one line
+ *   Find M--- and P-- → mixed prose + patterns
+ */
+function parsePatterns(text) {
+  const results = [];
+  const seen    = new Set();
+
+  // Single combined regex: captures "X---" optionally followed by " (N)"
+  // Minimum 2 dashes (so 3-letter minimum words).
+  const re = /([A-Z])(-+)(?:\s*\(\d+\))?/g;
+  let m;
+  while ((m = re.exec(text)) !== null) {
+    if (m[2].length < 2) continue; // skip single-dash noise
+    const pattern = (m[1] + m[2]).toUpperCase();
+    if (!seen.has(pattern)) {
+      seen.add(pattern);
+      results.push({ pattern });
+    }
+  }
+
+  return results;
+}
+
+/**
+ * Detect grid size hint from caption text.
+ * Returns a number (forced size) or null (let OCR auto-detect).
+ */
+function detectGridSizeFromCaption(text) {
+  const upper = text.toUpperCase();
+
+  // Explicit NxN e.g. "10x10" or "8x8"
+  const sizeMatch = text.match(/\b(\d+)\s*[xX×]\s*\1\b/);
+  if (sizeMatch) {
+    const n = parseInt(sizeMatch[1], 10);
+    if (n >= 4 && n <= 15) {
+      console.log(`[Grid] Caption explicit size: ${n}×${n}`);
+      return n;
+    }
+  }
+
+  if (
+    upper.includes('HARD MODE') ||
+    upper.includes('10X10') ||
+    upper.includes('10 X 10')
+  ) {
+    console.log('[Grid] Caption phrase → 10×10');
+    return 10;
+  }
+
+  return null; // let OCR auto-detect
+}
+
+// ─── Result formatter ──────────���──────────────────────────────────────────────
+function formatResults(results, grid, patterns) {
+  let msg = '🎯 <b>WORD GRID RESULTS</b>\n\n';
+  let foundAny = false;
+
+  for (const p of patterns) {
+    const key = p.pattern || p.word;
+    if (!key) continue;
+
+    const entry = results[key];
+    if (!entry) {
+      msg += `❓ ${key}: not found in grid\n`;
+      continue;
+    }
+
+    if (Array.isArray(entry)) {
+      // Pattern search — filter candidates against dictionary
+      const startChar = key[0].toUpperCase();
+      const wordMatches = new Set();
+
+      for (const hit of entry) {
+        const raw = hit.match.toUpperCase();
+
+        if (isWord(raw)) {
+          wordMatches.add(raw);
+          continue;
+        }
+
+        // OCR may have mis-read the first character — force the known start char
+        const forced = startChar + raw.slice(1);
+        if (isWord(forced)) {
+          wordMatches.add(forced);
+          continue;
+        }
+
+        console.log(`[Debug] Rejected non-word for "${key}": ${raw}`);
+      }
+
+      if (wordMatches.size > 0) {
+        const list = [...wordMatches].map(w => `<code>${w}</code>`).join(', ');
+        msg += `✅ ${key}: ${list}\n`;
+        stats.wordsFound += wordMatches.size;
+        foundAny = true;
+      } else {
+        msg += `❓ ${key}: no dictionary words matched\n`;
+      }
+    } else {
+      // Exact word search result
+      msg += `✅ <code>${entry.match}</code> @ [${entry.r},${entry.c}] ${entry.dir}\n`;
+      foundAny = true;
+    }
+  }
+
+  if (!foundAny) {
+    msg += '😔 No real word matches found for these patterns.\n';
+    msg += 'Tip: check that your caption patterns match the grid letters.\n';
+  }
+
+  // Always show the extracted grid for verification
+  msg += '\n🔍 <b>Extracted Grid:</b>\n';
+  msg += '<pre>' + grid.map(row => row.join(' ')).join('\n') + '</pre>';
+
+  return msg;
+}
+
+// ─── GramJS Bot ───────────────────────────────────────────────────────────────
+async function startBot() {
+  const session = new StringSession(''); // blank = new session each time (fine for bots)
+
+  const client = new TelegramClient(session, API_ID, API_HASH, {
+    connectionRetries: 10,
+    retryDelay:        2000,
+    autoReconnect:     true,
+    useWSS:            false,
+  });
+
+  console.log('[GramJS] Connecting via MTProto...');
+
+  await client.start({
+    botAuthToken: BOT_TOKEN,
+  });
+
+  console.log('[GramJS] Connected successfully.');
+
+  const me = await client.getMe();
+  stats.botUsername = me.username || 'bot';
+  console.log(`[Bot] Running as @${stats.botUsername}`);
+
+  // ── Message handler ──────────────────────────────────────────────────────────
+  client.addEventHandler(async (event) => {
+    const msg = event.message;
+    if (!msg) return;
+
+    const chatId  = msg.peerId;
+    const caption = (msg.message || '').trim();
+
+    // /start command
+    if (caption === '/start' || caption.startsWith('/start ')) {
+      await client.sendMessage(chatId, {
+        message: [
+          '👋 <b>Word Grid Solver Bot</b>',
+          '',
+          'Send me a word grid image with patterns in the caption.',
+          '',
+          '<b>Caption format:</b>',
+          '<code>M--- (4) P------- (8) S----- (6)</code>',
+          '',
+          '📐 Supports <b>8×8 and 10×10</b> grids (auto-detected)',
+          'Override with: <code>10x10</code> in caption',
+        ].join('\n'),
+        parseMode: 'html',
+      });
+      return;
+    }
+
+    // Only handle messages that carry a photo
+    const hasPhoto = msg.media && (
+      msg.media.className === 'MessageMediaPhoto' ||
+      (msg.media.document &&
+       msg.media.document.mimeType &&
+       msg.media.document.mimeType.startsWith('image/'))
+    );
+
+    if (!hasPhoto) return;
+
+    // ── Download image to disk via MTProto ─────────────────────────────────────
+    // GramJS downloadMedia accepts a STRING path as outputFile → writes file,
+    // returns the path. Do NOT pass Buffer constructor — that causes the
+    // "writer.write is not a function" error.
+    const imagePath = path.join(
+      __dirname,
+      `grid_${Date.now()}_${Math.random().toString(36).slice(2)}.jpg`
+    );
+
+    try {
+      await client.sendMessage(chatId, {
+        message: '🔍 Downloading and processing your grid image...',
+      });
+
+      // Pass the destination path string — GramJS streams the file there via MTProto
+      const result = await client.downloadMedia(msg, {
+        outputFile: imagePath,
+      });
+
+      // result is the path string when outputFile is a string path
+      if (!result) throw new Error('downloadMedia returned null/undefined');
+      if (!fs.existsSync(imagePath)) throw new Error('File not written to disk');
+
+      console.log(`[Download] Saved to ${imagePath} (${fs.statSync(imagePath).size} bytes)`);
+
+    } catch (dlErr) {
+      console.error('[Download] Failed:', dlErr.message);
+      await client.sendMessage(chatId, {
+        message: '❌ Failed to download the image. Please try again.',
+      });
+      await deleteFile(imagePath);
+      return;
+    }
+
+    // ── Process the image ──────────────────────────────────────────────────────
+    try {
+      stats.imagesProcessed++;
+
+      const forcedSize = detectGridSizeFromCaption(caption);
+
+      const grid = await extractGrid(imagePath, forcedSize);
+
+      if (!grid || grid.length === 0) {
+        await client.sendMessage(chatId, {
+          message: '❌ Could not extract a grid from the image.\nMake sure the grid letters are clearly visible.',
+        });
+        return;
+      }
+
+      const patterns = parsePatterns(caption);
+
+      if (patterns.length === 0) {
+        const noPatMsg =
+          '📋 <b>Grid extracted</b> (no patterns in caption):\n\n' +
+          '<pre>' + grid.map(r => r.join(' ')).join('\n') + '</pre>\n\n' +
+          'Add patterns like <code>M--- (4)</code> to find words!';
+        await client.sendMessage(chatId, { message: noPatMsg, parseMode: 'html' });
+        return;
+      }
+
+      const results = solve(grid, patterns);
+      const reply   = formatResults(results, grid, patterns);
+
+      await client.sendMessage(chatId, { message: reply, parseMode: 'html' });
+
+    } catch (err) {
+      console.error('[Handler] Processing error:', err);
+      await client.sendMessage(chatId, {
+        message: '🚨 An error occurred while processing. Please try again.',
+      });
+    } finally {
+      await deleteFile(imagePath);
+    }
+
+  }, new NewMessage({}));
+
+  console.log('[Bot] Listening for messages...');
+
+  // Graceful shutdown
+  const shutdown = async (sig) => {
+    console.log(`[Bot] ${sig} received — disconnecting...`);
+    try { await client.disconnect(); } catch (_) {}
+    process.exit(0);
+  };
+  process.once('SIGINT',  () => shutdown('SIGINT'));
+  process.once('SIGTERM', () => shutdown('SIGTERM'));
+}
+
+// ─── Express dashboard ────────────────────────────────────────────────────────
+const app  = express();
+const PORT = parseInt(process.env.PORT || '7860', 10);
+
+app.use(express.static(path.join(__dirname, 'public')));
+
+app.get('/api/stats', (_req, res) => {
+  res.json({
+    ...stats,
+    uptime: Math.floor((Date.now() - stats.startTime) / 1000),
+  });
+});
+
+app.listen(PORT, () => {
+  console.log(`[Dashboard] Running on port ${PORT}`);
+});
+
+// ─── Boot ─────────────────────────────────────────────────────────────────────
+startBot().catch(err => {
+  console.error('[FATAL] Bot startup failed:', err);
+  process.exit(1);
+});

ocr.js

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+/**
+ * ocr.js — Advanced multi-pass Tesseract OCR with auto-detecting grid size
+ *
+ * Key improvements over v1:
+ *  • Auto-detect grid size (8×8 vs 10×10 vs other NxN) via symbol clustering
+ *  • Multi-threshold voting (5 passes) for better letter accuracy
+ *  • K-means-style column/row centroid detection instead of fixed bucket math
+ *  • Lookalike-aware majority voting per cell (I/L, O/0, B/8, etc.)
+ *  • No magic assumption of exactly N symbols – works with noise/gaps
+ */
+
+const sharp = require('sharp');
+sharp.cache(false);
+const { createWorker } = require('tesseract.js');
+
+// ─── OCR lookalike corrections (applied at voting time) ───────────────────────
+const LOOKALIKE_GROUPS = [
+  ['I', 'L', '1', '|', 'J'],
+  ['O', '0', 'Q', 'D'],
+  ['B', '8', '3'],
+  ['S', '5'],
+  ['G', '6', 'C'],
+  ['Z', '2'],
+  ['E', 'F'],
+  ['U', 'V'],
+];
+
+// Build canonical map: non-alpha → preferred alpha
+const CANONICAL = {};
+for (const group of LOOKALIKE_GROUPS) {
+  const alpha = group.find(c => /^[A-Z]$/.test(c));
+  if (!alpha) continue;
+  for (const c of group) {
+    if (!/^[A-Z]$/.test(c)) CANONICAL[c] = alpha;
+  }
+}
+
+function canonicalise(char) {
+  return CANONICAL[char.toUpperCase()] || char.toUpperCase();
+}
+
+// ─── Simple 1-D k-means-style centroid finder ─────────────────────────────────
+/**
+ * Given a sorted list of values and a target cluster count,
+ * iteratively refine cluster centroids until stable.
+ * Returns sorted list of centroids.
+ */
+function findCentroids(values, k) {
+  if (values.length === 0) return [];
+  const sorted = [...values].sort((a, b) => a - b);
+  const min = sorted[0], max = sorted[sorted.length - 1];
+
+  if (k <= 1) return [(min + max) / 2];
+
+  // Initialise centroids evenly spaced
+  let centroids = Array.from({ length: k }, (_, i) => min + (i / (k - 1)) * (max - min));
+
+  for (let iter = 0; iter < 30; iter++) {
+    // Assign each value to nearest centroid
+    const clusters = Array.from({ length: k }, () => []);
+    for (const v of sorted) {
+      let best = 0, bestDist = Infinity;
+      for (let i = 0; i < k; i++) {
+        const d = Math.abs(v - centroids[i]);
+        if (d < bestDist) { bestDist = d; best = i; }
+      }
+      clusters[best].push(v);
+    }
+
+    // Recompute centroids
+    const newCentroids = centroids.map((c, i) => {
+      if (clusters[i].length === 0) return c;
+      return clusters[i].reduce((a, b) => a + b, 0) / clusters[i].length;
+    });
+
+    // Check convergence
+    const moved = newCentroids.some((nc, i) => Math.abs(nc - centroids[i]) > 0.01);
+    centroids = newCentroids;
+    if (!moved) break;
+  }
+
+  return centroids.sort((a, b) => a - b);
+}
+
+// ─── Auto-detect grid size from symbol cloud ──────────────────────────────────
+/**
+ * Try k=8 and k=10 clusterings on the X coordinates.
+ * Pick whichever produces tighter within-cluster variance.
+ */
+function detectGridSize(xs) {
+  if (xs.length === 0) return 8;
+
+  const tryK = (k) => {
+    const cents = findCentroids(xs, k);
+    let totalVar = 0;
+    const clusters = Array.from({ length: k }, () => []);
+    for (const x of xs) {
+      let best = 0, bestDist = Infinity;
+      for (let i = 0; i < k; i++) {
+        const d = Math.abs(x - cents[i]);
+        if (d < bestDist) { bestDist = d; best = i; }
+      }
+      clusters[best].push(x);
+    }
+    for (const cl of clusters) {
+      if (cl.length === 0) continue;
+      const mean = cl.reduce((a, b) => a + b, 0) / cl.length;
+      totalVar += cl.reduce((s, v) => s + (v - mean) ** 2, 0);
+    }
+    // Normalise by k so we compare fairly
+    return totalVar / k;
+  };
+
+  // If very few symbols, default to 8
+  if (xs.length < 30) return 8;
+
+  const v8  = tryK(8);
+  const v10 = tryK(10);
+
+  // Heuristic: also check symbol density
+  // A 10×10 grid should have ~100 symbols; an 8×8 ~ 64
+  const symbolCount = xs.length;
+  if (symbolCount > 350) return 10; // many multi-pass hits → likely 10×10
+
+  // Use variance ratio to decide
+  // If v10 is significantly better (lower) than v8, go with 10
+  return (v10 < v8 * 0.85) ? 10 : 8;
+}
+
+// ─── Main extractGrid function ────────────────────────────────────────────────
+/**
+ * @param {string} imagePath
+ * @param {number|null} forcedSize  - if null, auto-detect
+ * @returns {string[][]|null}
+ */
+async function extractGrid(imagePath, forcedSize = null) {
+  let worker = null;
+  try {
+    const THRESHOLDS = [70, 100, 130, 160, 190, 210];
+    const allSymbols = []; // { char, x, y }
+
+    worker = await createWorker('eng');
+    await worker.setParameters({
+      tessedit_char_whitelist: 'ABCDEFGHIJKLMNOPQRSTUVWXYZ',
+      tessedit_pageseg_mode: '6', // Assume uniform block of text
+    });
+
+    for (const th of THRESHOLDS) {
+      let buf;
+      try {
+        buf = await sharp(imagePath)
+          .grayscale()
+          .normalize()
+          .sharpen({ sigma: 1.5 })
+          .threshold(th)
+          .toBuffer();
+      } catch (e) {
+        console.warn(`Sharp preprocessing failed at threshold ${th}:`, e.message);
+        continue;
+      }
+
+      let res;
+      try {
+        res = await worker.recognize(buf);
+      } catch (e) {
+        console.warn(`Tesseract failed at threshold ${th}:`, e.message);
+        continue;
+      }
+
+      if (!res.data.symbols) continue;
+
+      for (const s of res.data.symbols) {
+        const raw = (s.text || '').replace(/[^A-Za-z0-9|]/g, '').toUpperCase();
+        if (!raw || raw.length !== 1) continue;
+        const ch = canonicalise(raw);
+        if (!/^[A-Z]$/.test(ch)) continue;
+
+        const midX = (s.bbox.x0 + s.bbox.x1) / 2;
+        const midY = (s.bbox.y0 + s.bbox.y1) / 2;
+        allSymbols.push({ char: ch, x: midX, y: midY });
+      }
+    }
+
+    await worker.terminate();
+    worker = null;
+
+    if (allSymbols.length === 0) {
+      console.warn('No symbols detected from OCR.');
+      return null;
+    }
+
+    console.log(`Total symbol observations (all passes): ${allSymbols.length}`);
+
+    // ── Detect or use forced grid size ──
+    const xs = allSymbols.map(s => s.x);
+    const ys = allSymbols.map(s => s.y);
+
+    const gridSize = forcedSize !== null ? forcedSize : detectGridSize(xs);
+    console.log(`Using grid size: ${gridSize}×${gridSize}`);
+
+    // ── Cluster columns and rows ──
+    const colCentroids = findCentroids(xs, gridSize);
+    const rowCentroids = findCentroids(ys, gridSize);
+
+    // ── Vote per cell ──
+    // cellVotes[r][c] = { char: count }
+    const cellVotes = Array.from({ length: gridSize }, () =>
+      Array.from({ length: gridSize }, () => ({}))
+    );
+
+    const colSpan = colCentroids.length > 1
+      ? (colCentroids[colCentroids.length - 1] - colCentroids[0]) / (gridSize - 1)
+      : 50;
+    const rowSpan = rowCentroids.length > 1
+      ? (rowCentroids[rowCentroids.length - 1] - rowCentroids[0]) / (gridSize - 1)
+      : 50;
+    const colTol = colSpan * 0.5;
+    const rowTol = rowSpan * 0.5;
+
+    for (const s of allSymbols) {
+      // Assign to nearest column centroid within tolerance
+      let bestC = -1, bestCDist = Infinity;
+      for (let i = 0; i < colCentroids.length; i++) {
+        const d = Math.abs(s.x - colCentroids[i]);
+        if (d < bestCDist) { bestCDist = d; bestC = i; }
+      }
+      if (bestCDist > colTol * 2) continue; // too far from any centroid → noise
+
+      let bestR = -1, bestRDist = Infinity;
+      for (let i = 0; i < rowCentroids.length; i++) {
+        const d = Math.abs(s.y - rowCentroids[i]);
+        if (d < bestRDist) { bestRDist = d; bestR = i; }
+      }
+      if (bestRDist > rowTol * 2) continue;
+
+      cellVotes[bestR][bestC][s.char] = (cellVotes[bestR][bestC][s.char] || 0) + 1;
+    }
+
+    // ── Build final grid ──
+    const grid = Array.from({ length: gridSize }, (_, r) =>
+      Array.from({ length: gridSize }, (_, c) => {
+        const votes = cellVotes[r][c];
+        let best = '?', maxV = 0;
+        for (const [ch, v] of Object.entries(votes)) {
+          if (v > maxV) { maxV = v; best = ch; }
+        }
+        return best;
+      })
+    );
+
+    // Log the extracted grid for debugging
+    console.log('Extracted grid:');
+    for (const row of grid) {
+      console.log(row.join(' '));
+    }
+
+    return grid;
+  } catch (err) {
+    console.error('OCR Error:', err);
+    if (worker) {
+      try { await worker.terminate(); } catch (_) {}
+    }
+    return null;
+  }
+}
+
+module.exports = { extractGrid };

ocr.py

@@ -0,0 +1,108 @@
+import easyocr
+import easyocr.easyocr
+import sys
+import json
+import os
+from PIL import Image
+import io
+
+# Fix EasyOCR bug
+easyocr.easyocr.corrupt_msg = "Model error"
+
+def process_image(reader, image_path):
+    try:
+        if not os.path.exists(image_path):
+            return {"error": f"Path not found: {image_path}"}
+
+        # Single-pass OCR is much faster and usually accurate enough for Deep Learning models
+        results = reader.readtext(image_path, detail=1)
+        if not results:
+             return {"error": "No text detected"}
+
+        symbols = []
+        for (bbox, text, prob) in results:
+            text = text.strip().upper()
+            clean_text = "".join([c for c in text if c.isalpha()])
+            if not clean_text: continue
+            
+            x_center = (bbox[0][0] + bbox[2][0]) / 2
+            y_center = (bbox[0][1] + bbox[2][1]) / 2
+            
+            if len(clean_text) > 1:
+                # Approximate positions for concatenated chars
+                w = bbox[2][0] - bbox[0][0]
+                char_w = w / len(clean_text)
+                for i, char in enumerate(clean_text):
+                    symbols.append({
+                        "text": char,
+                        "x": bbox[0][0] + (i + 0.5) * char_w,
+                        "y": y_center
+                    })
+            else:
+                symbols.append({"text": clean_text, "x": x_center, "y": y_center})
+
+        if not symbols: return []
+
+        # Find 8 distinct lanes for X and Y
+        def get_lanes(coords, num_lanes=8):
+            coords.sort()
+            if not coords: return []
+            lanes = []
+            # Simple clustering: divide range into 8 buckets
+            mi, ma = min(coords), max(coords)
+            if ma == mi: return [mi]
+            
+            bucket_size = (ma - mi) / (num_lanes - 1) if num_lanes > 1 else 1
+            for i in range(num_lanes):
+                center = mi + i * bucket_size
+                lanes.append(center)
+            return lanes
+
+        xs = [s["x"] for s in symbols]
+        ys = [s["y"] for s in symbols]
+        
+        x_lanes = get_lanes(xs, 8)
+        y_lanes = get_lanes(ys, 8)
+        
+        grid = [[" " for _ in range(8)] for _ in range(8)]
+        for s in symbols:
+            # Map to nearest lane
+            r = min(range(8), key=lambda i: abs(s["y"] - y_lanes[i]))
+            c = min(range(8), key=lambda i: abs(s["x"] - x_lanes[i]))
+            grid[r][c] = s["text"]
+
+        final_symbols = []
+        for r in range(8):
+            for c in range(8):
+                if grid[r][c] != " ":
+                    final_symbols.append({"text": grid[r][c], "r": r, "c": c})
+        return final_symbols
+                    
+    except Exception as e:
+        return {"error": str(e)}
+
+def main():
+    # Initialize reader ONCE
+    try:
+        reader = easyocr.Reader(['en'], gpu=False, verbose=False)
+        # Signal ready
+        print("READY", flush=True)
+    except Exception as e:
+        print(json.dumps({"error": f"Init failed: {str(e)}"}), flush=True)
+        return
+
+    # Listen for image paths on stdin
+    while True:
+        line = sys.stdin.readline()
+        if not line:
+            break
+        
+        image_path = line.strip()
+        if not image_path:
+            continue
+            
+        result = process_image(reader, image_path)
+        print(json.dumps(result), flush=True)
+
+if __name__ == "__main__":
+    main()

package-lock.json

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package.json

@@ -0,0 +1,21 @@
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+  "name": "wordgridsolver",
+  "version": "2.0.0",
+  "description": "Telegram bot (GramJS MTProto) to solve 8x8 and 10x10 word grid puzzles",
+  "main": "bot.js",
+  "scripts": {
+    "start": "node bot.js",
+    "test": "node -e \"const {solve}=require('./solver'); console.log('Solver OK');\""
+  },
+  "dependencies": {
+    "axios": "^1.6.0",
+    "check-word": "^1.1.0",
+    "dotenv": "^17.4.2",
+    "express": "^5.2.1",
+    "sharp": "^0.34.5",
+    "telegram": "^2.26.0",
+    "tesseract.js": "^5.0.0",
+    "input": "^1.0.1",
+    "big-integer": "^1.6.52"
+  }
+}

public/index.html

@@ -0,0 +1,224 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Word Grid Solver - Dashboard</title>
+    <link href="https://fonts.googleapis.com/css2?family=Outfit:wght@300;400;600;800&display=swap" rel="stylesheet">
+    <style>
+        :root {
+            --bg: #0a0a0c;
+            --accent: #6c5ce7;
+            --accent-glow: rgba(108, 92, 231, 0.3);
+            --card-bg: rgba(255, 255, 255, 0.03);
+            --text: #ffffff;
+            --secondary-text: #a0a0a8;
+        }
+
+        body {
+            margin: 0;
+            padding: 0;
+            font-family: 'Outfit', sans-serif;
+            background-color: var(--bg);
+            color: var(--text);
+            display: flex;
+            flex-direction: column;
+            align-items: center;
+            justify-content: center;
+            min-height: 100vh;
+            overflow: hidden;
+        }
+
+        .background-blob {
+            position: absolute;
+            width: 600px;
+            height: 600px;
+            background: radial-gradient(circle, var(--accent-glow) 0%, transparent 70%);
+            z-index: -1;
+            filter: blur(50px);
+            animation: move 20s infinite alternate linear;
+        }
+
+        @keyframes move {
+            from {
+                transform: translate(-20%, -20%);
+            }
+
+            to {
+                transform: translate(20%, 20%);
+            }
+        }
+
+        .container {
+            width: 90%;
+            max-width: 600px;
+            text-align: center;
+            backdrop-filter: blur(10px);
+            padding: 40px;
+            border-radius: 30px;
+            background: var(--card-bg);
+            border: 1px solid rgba(255, 255, 255, 0.05);
+            box-shadow: 0 10px 40px rgba(0, 0, 0, 0.5);
+            animation: fadeIn 1s ease-out;
+        }
+
+        @keyframes fadeIn {
+            from {
+                opacity: 0;
+                transform: translateY(20px);
+            }
+
+            to {
+                opacity: 1;
+                transform: translateY(0);
+            }
+        }
+
+        h1 {
+            font-size: 2.5rem;
+            font-weight: 800;
+            margin-bottom: 10px;
+            background: linear-gradient(135deg, #fff 0%, var(--accent) 100%);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+        }
+
+        .bot-username {
+            font-size: 1.2rem;
+            color: var(--accent);
+            font-weight: 600;
+            margin-bottom: 30px;
+            display: inline-block;
+            background: var(--accent-glow);
+            padding: 5px 15px;
+            border-radius: 100px;
+            border: 1px solid var(--accent);
+        }
+
+        .stats-grid {
+            display: grid;
+            grid-template-columns: repeat(3, 1fr);
+            gap: 20px;
+            margin-top: 20px;
+        }
+
+        .stat-card {
+            background: rgba(255, 255, 255, 0.03);
+            padding: 20px;
+            border-radius: 20px;
+            border: 1px solid rgba(255, 255, 255, 0.05);
+            transition: transform 0.3s ease;
+        }
+
+        .stat-card:hover {
+            transform: translateY(-5px);
+            background: rgba(255, 255, 255, 0.05);
+        }
+
+        .stat-value {
+            font-size: 1.8rem;
+            font-weight: 600;
+            display: block;
+            margin-bottom: 5px;
+        }
+
+        .stat-label {
+            font-size: 0.8rem;
+            color: var(--secondary-text);
+            text-transform: uppercase;
+            letter-spacing: 1px;
+        }
+
+        .footer {
+            margin-top: 50px;
+            color: var(--secondary-text);
+            font-size: 0.9rem;
+        }
+
+        .credits {
+            font-weight: 600;
+            color: #fff;
+            letter-spacing: 0.5px;
+        }
+
+        .status-dot {
+            width: 10px;
+            height: 10px;
+            background-color: #00ff88;
+            border-radius: 50%;
+            display: inline-block;
+            margin-right: 8px;
+            box-shadow: 0 0 10px #00ff88;
+            animation: pulse 2s infinite;
+        }
+
+        @keyframes pulse {
+            0% {
+                opacity: 1;
+            }
+
+            50% {
+                opacity: 0.5;
+            }
+
+            100% {
+                opacity: 1;
+            }
+        }
+    </style>
+</head>
+
+<body>
+    <div class="background-blob"></div>
+    <div class="container">
+        <div style="margin-bottom: 20px;">
+            <span class="status-dot"></span> <b>Bot Active</b>
+        </div>
+        <h1>Word Grid Solver</h1>
+        <div class="bot-username" id="bot-handle">@loading...</div>
+
+        <div class="stats-grid">
+            <div class="stat-card">
+                <span class="stat-value" id="stats-images">0</span>
+                <span class="stat-label">Scanned</span>
+            </div>
+            <div class="stat-card">
+                <span class="stat-value" id="stats-words">0</span>
+                <span class="stat-label">Words</span>
+            </div>
+            <div class="stat-card">
+                <span class="stat-value" id="stats-uptime">0s</span>
+                <span class="stat-label">Uptime</span>
+            </div>
+        </div>
+
+        <div class="footer">
+            wordsgrid solver by <span class="credits">alexainc</span>
+        </div>
+    </div>
+
+    <script>
+        function updateStats() {
+            fetch('/api/stats')
+                .then(r => r.json())
+                .then(data => {
+                    document.getElementById('bot-handle').innerText = 't.me/' + data.botUsername;
+                    document.getElementById('stats-images').innerText = data.imagesProcessed;
+                    document.getElementById('stats-words').innerText = data.wordsFound;
+
+                    const uptime = data.uptime;
+                    let uptimeStr = uptime + 's';
+                    if (uptime > 3600) uptimeStr = Math.floor(uptime / 3600) + 'h';
+                    else if (uptime > 60) uptimeStr = Math.floor(uptime / 60) + 'm';
+
+                    document.getElementById('stats-uptime').innerText = uptimeStr;
+                });
+        }
+
+        setInterval(updateStats, 2000);
+        updateStats();
+    </script>
+</body>
+
+</html>

solver.js

@@ -0,0 +1,212 @@
+/**
+ * solver.js — Word Grid solver with comprehensive lookalike tolerance
+ *
+ * Improvements over v1:
+ *  • Symmetric LOOKALIKES map (A→B implies B can match A)
+ *  • Wildcard (-) pattern matching ignores only dashes, not all unknowns
+ *  • Pattern matching collects ALL candidates with their actual grid characters
+ *  • charMatch is stricter: only matches confirmed lookalike pairs, not random guesses
+ *  • Grid boundary checks are consolidated in one place (no off-by-one)
+ *  • Deduplication of candidates by match string
+ */
+
+// ─── Directions ───────────────────────────────────────────────────────────────
+const DIRECTIONS = [
+  { r: 0,  c:  1, name: 'LtoR'  },
+  { r: 0,  c: -1, name: 'RtoL'  },
+  { r: 1,  c:  0, name: 'UtoD'  },
+  { r: -1, c:  0, name: 'DtoU'  },
+  { r: 1,  c:  1, name: 'diagDR'},
+  { r: -1, c: -1, name: 'diagUL'},
+  { r: 1,  c: -1, name: 'diagDL'},
+  { r: -1, c:  1, name: 'diagUR'},
+];
+
+// ─── Lookalike table (symmetric) ─────────────────────────────────────────────
+// Each entry lists chars that can be confused FOR the key char by OCR.
+const LOOKALIKES_RAW = {
+  'A': ['4', 'R'],
+  'B': ['8', '3', 'R', 'S', 'E'],
+  'C': ['G', 'O', 'Q', '(', 'L'],
+  'D': ['O', 'Q', 'B', '0'],
+  'E': ['F', 'B', '3', 'L'],
+  'F': ['E', 'P'],
+  'G': ['C', 'O', '6', 'Q', 'D'],
+  'H': ['N', 'M'],
+  'I': ['L', '1', 'T', 'J', '|'],
+  'J': ['I', 'L', '1'],
+  'K': ['R', 'X'],
+  'L': ['I', '1', 'T', '|', '[', 'J'],
+  'M': ['N', 'H', 'W'],
+  'N': ['M', 'H', 'R'],
+  'O': ['0', 'Q', 'G', 'C', 'D', 'U'],
+  'P': ['F', 'B', 'R'],
+  'Q': ['O', 'G', 'C', '0'],
+  'R': ['B', 'P', 'K', 'I', 'A', 'N'],
+  'S': ['5', '8', 'B', '6'],
+  'T': ['I', 'L', '7', '+'],
+  'U': ['V', 'W', 'O', 'Y'],
+  'V': ['U', 'Y', 'W'],
+  'W': ['M', 'V', 'U'],
+  'X': ['K', 'Y'],
+  'Y': ['V', 'U', 'X'],
+  'Z': ['2', '7'],
+};
+
+// Build symmetric version: if A can be confused as B, then B can be confused as A
+const LOOKALIKES = {};
+for (const [key, alts] of Object.entries(LOOKALIKES_RAW)) {
+  if (!LOOKALIKES[key]) LOOKALIKES[key] = new Set();
+  for (const alt of alts) {
+    LOOKALIKES[key].add(alt);
+    // symmetric
+    if (/^[A-Z]$/.test(alt)) {
+      if (!LOOKALIKES[alt]) LOOKALIKES[alt] = new Set();
+      LOOKALIKES[alt].add(key);
+    }
+  }
+}
+
+/**
+ * Does `gridChar` match `targetChar` considering OCR lookalikes?
+ * Both must be non-empty, non-space.
+ */
+function charMatch(target, gridChar) {
+  if (!gridChar || gridChar === ' ' || gridChar === '?') return false;
+  const t = target.toUpperCase();
+  const g = gridChar.toUpperCase();
+  if (t === g) return true;
+  const alts = LOOKALIKES[t];
+  return !!(alts && alts.has(g));
+}
+
+/**
+ * Check all cells are in bounds on a grid
+ */
+function inBounds(grid, r, c) {
+  return r >= 0 && r < grid.length && c >= 0 && c < (grid[r] ? grid[r].length : 0);
+}
+
+/**
+ * Solve the grid for a list of word/pattern objects.
+ *
+ * Each item in `words` is one of:
+ *   { word: 'MATRIX' }           → exact word search
+ *   { pattern: 'M---' }          → pattern search (first char + length)
+ *
+ * Returns an object:
+ *   { 'M---': [ { r, c, dir, match, reliable } ], ... }
+ *   { 'MATRIX': { r, c, dir, match } }
+ */
+function solve(grid, words) {
+  const results = {};
+  const rows = grid.length;
+  if (rows === 0) return results;
+
+  for (const wordObj of words) {
+    const isExact = wordObj.word && !wordObj.word.includes('-');
+    const isPattern = !!wordObj.pattern;
+
+    if (isExact) {
+      const target = wordObj.word.toUpperCase();
+      const len = target.length;
+      let found = false;
+
+      outer:
+      for (let r = 0; r < rows && !found; r++) {
+        const cols = grid[r].length;
+        for (let c = 0; c < cols && !found; c++) {
+          if (!charMatch(target[0], grid[r][c])) continue;
+          for (const dir of DIRECTIONS) {
+            // Quick bounds check for last character
+            const er = r + dir.r * (len - 1);
+            const ec = c + dir.c * (len - 1);
+            if (!inBounds(grid, er, ec)) continue;
+
+            let match = true;
+            let candidate = '';
+            for (let i = 0; i < len; i++) {
+              const nr = r + dir.r * i;
+              const nc = c + dir.c * i;
+              if (!inBounds(grid, nr, nc) || !charMatch(target[i], grid[nr][nc])) {
+                match = false;
+                break;
+              }
+              candidate += grid[nr][nc];
+            }
+            if (match) {
+              results[wordObj.word] = { r, c, dir: dir.name, match: candidate };
+              found = true;
+              break;
+            }
+          }
+        }
+      }
+    } else if (isPattern) {
+      const pattern = wordObj.pattern.toUpperCase(); // e.g. "M---"
+      const startChar = pattern[0];
+      const len = pattern.length;
+      const hits = [];
+
+      for (let r = 0; r < rows; r++) {
+        const cols = grid[r].length;
+        for (let c = 0; c < cols; c++) {
+          if (!charMatch(startChar, grid[r][c])) continue;
+
+          for (const dir of DIRECTIONS) {
+            // Bounds check for last char
+            const er = r + dir.r * (len - 1);
+            const ec = c + dir.c * (len - 1);
+            if (!inBounds(grid, er, ec)) continue;
+
+            let possible = true;
+            let candidate = '';
+            for (let i = 0; i < len; i++) {
+              const nr = r + dir.r * i;
+              const nc = c + dir.c * i;
+              if (!inBounds(grid, nr, nc)) { possible = false; break; }
+              const ch = grid[nr][nc];
+              if (!ch || ch === ' ') { possible = false; break; }
+              candidate += ch;
+            }
+
+            if (possible && candidate.length === len) {
+              hits.push({ r, c, dir: dir.name, match: candidate });
+            }
+          }
+        }
+      }
+
+      // Deduplicate by match string
+      const seen = new Set();
+      const unique = hits.filter(h => {
+        if (seen.has(h.match)) return false;
+        seen.add(h.match);
+        return true;
+      });
+
+      if (unique.length > 0) results[pattern] = unique;
+    }
+  }
+
+  return results;
+}
+
+// ─── Leaderboard ──────────────────────────────────────────────────────────────
+let leaderboard = [];
+
+function getWordScore(word) {
+  return word.length * 10;
+}
+
+function recordScore(userName, score) {
+  leaderboard.push({ name: userName, score, date: new Date().toISOString() });
+  leaderboard.sort((a, b) => b.score - a.score);
+  leaderboard = leaderboard.slice(0, 10);
+}
+
+function getLeaderboard() {
+  return leaderboard;
+}
+
+module.exports = { solve, charMatch, getWordScore, recordScore, getLeaderboard };